NCBI Papers with Code

List of awesome NCBI Papers with Code Supplement.

CNN

  1. Dual CNN for Relation Extraction with Knowledge-Based Attention and Word Embeddings Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6664687/ Code: https://github.com/mrlijun2017/Dual-CNN-RE

  2. CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classes Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751796/ Code: https://github.com/whiteclarence/CNN-BLPred

  3. Design of deep convolutional networks for prediction of image rapid serial visual presentation events Paper: https://www.ncbi.nlm.nih.gov/pubmed/29060296 Code: https://github.com/ZijingMao/ROICNN

  4. A simple convolutional neural network for prediction of enhancer-promoter interactions with DNA sequence data Paper: https://www.ncbi.nlm.nih.gov/pubmed/30649185 Code: https://github.com/zzUMN/Combine-CNN-Enhancer-and-Promoters

  5. A novel attention-based hybrid CNN-RNN architecture for sEMG-based gesture recognition Paper:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6207326/ Code: https://github.com/biopatrec/biopatrec

  6. GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text Paper: https://www.ncbi.nlm.nih.gov/pubmed/29272325 Code: https://github.com/valdersoul/GRAM-CNN

  7. Simple tricks of convolutional neural network architectures improve DNA-protein binding prediction Paper: https://www.ncbi.nlm.nih.gov/pubmed/30351403 Code: https://github.com/zhanglabtools/DNADataAugmentation

  8. EnzyNet: enzyme classification using 3D convolutional neural networks on spatial representation Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5937476/ Code: https://github.com/shervinea/enzynet

  9. Multi-timescale drowsiness characterization based on a video of a driver's face Paper: https://www.telecom.ulg.ac.be/mts-drowsiness/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165048/ Code: https://github.com/QMassoz/mts-drowsiness

  10. CLoDSA: a tool for augmentation in classification, localization, detection, semantic segmentation and instance segmentation tasks Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567576/ Code: https://github.com/joheras/CLoDSA

  11. Deep learning with convolutional neural networks for EEG decoding and visualization Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5655781/ Code: https://github.com/robintibor/braindecode/ Code: https://github.com/TNTLFreiburg/braindecode

Rice/Paddy Classification

  1. Classifying Oryza sativa accessions into Indica and Japonica using logistic regression model with phenotypic data Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6842562/ Code: https://github.com/bongsongkim/logit.regression.rice

  2. SNNRice6mA: A Deep Learning Method for Predicting DNA N6-Methyladenine Sites in Rice Genome Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797597/ Code: https://github.com/yuht4/SNNRice6mA

  3. Automatic estimation of heading date of paddy rice using deep learning Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6626381/ Code: https://github.com/svdesai/heading-date-estimation

  4. Distillation of crop models to learn plant physiology theories using machine learning Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6541271/ Code: https://github.com/ky0on/simriw

  5. Evaluating remote sensing datasets and machine learning algorithms for mapping plantations and successional forests in Phnom Kulen National Park of Cambodia Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6814064/ Code: https://github.com/Jojo666/PKNP-Data

  6. PlantCV v2: Image analysis software for high-throughput plant phenotyping Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5713628/ Code: https://github.com/danforthcenter/plantcv-v2-paper

  7. Crop Yield Prediction Using Deep Neural Networks Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6540942/ Code: https://github.com/saeedkhaki92/Yield-Prediction-DNN

  8. Using Deep Learning for Image-Based Plant Disease Detection Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5032846/ Code: https://github.com/salathegroup/plantvillage_deeplearning_paper_analysis

  9. Deep Plant Phenomics: A Deep Learning Platform for Complex Plant Phenotyping Tasks Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5500639/ Code: https://github.com/p2irc/deepplantphenomics

  10. DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning Paper: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375952/ Code: https://github.com/AlexOlsen/DeepWeeds